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Articles 1 - 3 of 3
Full-Text Articles in Medicine and Health Sciences
Bioelectric Applications For Treatment Of Melanoma, Stephen J. Beebe, Karl H. Schoenbach, Richard Heller
Bioelectric Applications For Treatment Of Melanoma, Stephen J. Beebe, Karl H. Schoenbach, Richard Heller
Bioelectrics Publications
Two new cancer therapies apply bioelectric principles. These methods target tumor structures locally and function by applying millisecond electric fields to deliver plasmid DNA encoding cytokines using electrogene transfer (EGT) or by applying rapid rise-time nanosecond pulsed electric fields (nsPEFs). EGT has been used to locally deliver cytokines such as IL-12 to activate an immune response, resulting in bystander effects. NsPEFs locally induce apoptosis-like effects and affect vascular networks, both promoting tumor demise and restoration of normal vascular homeostasis. EGT with IL-12 is in melanoma clinical trials and nsPEFs are used in models with B16F10 melanoma in vitro and in …
Prostate Cancer Region Prediction Using Maldi Mass Spectra, Ayyappa Vadlamudi, Shao-Hui Chuang, Xiaoyan Sun, Lisa Cazares, Julius Nyalwidhe, Dean Troyer, O. John Semmes, Jiang Li, Frederic D. Mckenzie
Prostate Cancer Region Prediction Using Maldi Mass Spectra, Ayyappa Vadlamudi, Shao-Hui Chuang, Xiaoyan Sun, Lisa Cazares, Julius Nyalwidhe, Dean Troyer, O. John Semmes, Jiang Li, Frederic D. Mckenzie
Electrical & Computer Engineering Faculty Publications
For the early detection of prostate cancer, the analysis of the Prostate-specific antigen (PSA) in serum is currently the most popular approach. However, previous studies show that 15% of men have prostate cancer even their PSA concentrations are low. MALDI Mass Spectrometry (MS) proves to be a better technology to discover molecular tools for early cancer detection. The molecular tools or peptides are termed as biomarkers. Using MALDI MS data from prostate tissue samples, prostate cancer biomarkers can be identified by searching for molecular or molecular combination that can differentiate cancer tissue regions from normal ones. Cancer tissue regions are …
Prediction Of Brain Tumor Progression Using A Machine Learning Technique, Yuzhong Shen, Debrup Banerjee, Jiang Li, Adam Chandler, Yufei Shen, Frederic D. Mckenzie, Jihong Wang, Nico Karssemeijer (Ed.), Ronald M. Summers (Ed.)
Prediction Of Brain Tumor Progression Using A Machine Learning Technique, Yuzhong Shen, Debrup Banerjee, Jiang Li, Adam Chandler, Yufei Shen, Frederic D. Mckenzie, Jihong Wang, Nico Karssemeijer (Ed.), Ronald M. Summers (Ed.)
Electrical & Computer Engineering Faculty Publications
A machine learning technique is presented for assessing brain tumor progression by exploring six patients' complete MRI records scanned during their visits in the past two years. There are ten MRI series, including diffusion tensor image (DTI), for each visit. After registering all series to the corresponding DTI scan at the first visit, annotated normal and tumor regions were overlaid. Intensity value of each pixel inside the annotated regions were then extracted across all of the ten MRI series to compose a 10 dimensional vector. Each feature vector falls into one of three categories:normal, tumor, and normal but progressed to …